Metadata-Version: 2.1
Name: squlearn
Version: 0.2.0
Summary: A library for quantum machine learning following the sklearn standard.
Keywords: quantum,machine learning,qml
Author-email: David Kreplin <david.kreplin@ipa.fraunhofer.de>, Frederic Rapp <frederic.rapp@ipa.fraunhofer.de>, Marco Roth <marco.roth@ipa.fraunhofer.de>, Jan Schnabel <jan.schnabel@ipa.fraunhofer.de>, Moritz Willmann <moritz.willmann@ipa.fraunhofer.de>
Maintainer-email: David Kreplin <david.kreplin@ipa.fraunhofer.de>, Moritz Willmann <moritz.willmann@ipa.fraunhofer.de>
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Dist: numpy>=1.17
Requires-Dist: scipy>=1.5
Requires-Dist: scikit-learn>=1.0
Requires-Dist: qiskit>=0.42.1
Requires-Dist: qiskit-machine-learning>=0.6.0
Requires-Dist: qiskit-ibm-runtime>=0.9
Requires-Dist: dill>=0.3
Requires-Dist: pylint ; extra == "dev"
Requires-Dist: black ; extra == "dev"
Requires-Dist: pytest ; extra == "dev"
Requires-Dist: sphinx ; extra == "dev"
Requires-Dist: sphinx-rtd-theme ; extra == "dev"
Requires-Dist: flit ; extra == "dev"
Requires-Dist: jupyter ; extra == "examples"
Requires-Dist: matplotlib>=3.5 ; extra == "examples"
Requires-Dist: pylatexenc>=2.10 ; extra == "examples"
Project-URL: Homepage, https://github.com/sQUlearn/squlearn
Provides-Extra: dev
Provides-Extra: examples

# sQUlearn 0.2.0

**_Note:_** This is an early access version! Not everything that is described is already working 100%.

## Prerequisites

The package requires **at least Python 3.9**.
## Installation

### Stable Release

To install the stable release version of sQUlearn, run the following command:
```bash
pip install squlearn
```

Alternatively, you can install sQUlearn directly from GitHub via
```bash
pip install git+ssh://git@github.com:sQUlearn/squlearn.git
```

## Examples
There are several more elaborate examples available in the folder ``./examples`` which display the features of this package.
Tutorials for beginners can be found at ``./examples/tutorials``.

To install the required packages, run
```bash
pip install .[examples]
```

## Contribution
Thanks for considering to contribute to sQUlearn! Please read our [contribution guidelines](./.github/CONTRIBUTING.md) before you submit a pull request.

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## License

[Apache License 2.0](https://github.com/sQUlearn/squlearn/blob/main/LICENSE.txt)

## Imprint
This project is maintained by the quantum computing group at the Fraunhofer Institute for Manufacturing Engineering and Automation IPA. It started as a collection of implementations of quantum machine learning methods.

http://www.ipa.fraunhofer.de/quantum

---

